Objective To analyze the differences between the new and old versions of GB/T 7247.1-2024 and GB 7247.1-2012 of “Safety of laser products-Part 1: equipment classification and requirements”, and to facilitate manufacturers and inspectors of laser medical devices in understanding the new version of the standard. Methods By combining common parameters and conditions in practical inspections, the significant changes in the new version of the standard were analyzed. Results In aspects of great concern for inspections, compared to the old version, the new version has undergone major changes in laser classification, measurement and evaluation conditions, accessible emission limits, maximum on-axis angle, external marking, and other aspects. Conclusion The new version of the standard incorporates more scientific data and has made more detailed revisions and improvements to multiple parameters, making it more aligned with actual situations. Through the analysis of the key changes of the new version of the standard, it will help to promote the development of the standardization process in this field.

Objective To design a visualized medical service platform for cardiothoracic surgery as to optimize the efficiency of doctor-patient communication and personalized diagnosis and treatment. Methods Based on the Swin-UNet model, multi-organ segmentation was performed on thoracic CT images. Combined with the VTK algorithm, three-dimensional visualization images were generated to construct a visual medical service platform. The treatment plan understanding score, knowledge mastery rate, communication time and satisfaction of patients in the experimental group (using the platform) and the control group (not using the platform) were compared. Results Compared with the control group, there were statistically significant differences in the experimental group of treatment plan understanding score of the diagnosis and treatment plan [(4.60±0.50) points vs. (3.40±0.70) points, P<0.001], the knowledge mastery rate (72.60%±6.20% vs. 38.70%±8.50%, P<0.001), satisfaction of the patients in the experimental group [(4.70±0.40) points vs. (3.80±0.60) points, P<0.001], and the communication time of diagnosis and treatment [(12.40±2.10) min vs. (18.20±3.50) min] was significantly shortened (P<0.05). Conclusion The visual medical service platform constructed based on the Swin-UNet deep learning model and VTK ray projection algorithm, integrating 3D modeling and artificial intelligence technology, can provide scientific basis and practical support for optimizing doctor-patient communication, improving diagnosis and treatment efficiency, and promoting personalized and precise medicine.

Objective In order to enhance the efficiency and accuracy of extracting unstructured information from clinical case texts and promote the intelligent development of medicine, to propose a case text structured model based on the bidirectional encoder representations from transformers fusion algorithm. Methods In this model, bidirectional encoder was used for semantic representation, graph convolutional neural network was used to extract local dependencies between words, long short-term memory network was used to establish temporal relation, and conditional random field was introduced to optimize the consistency of label sequence. Two authoritative clinical datasets, MIMIC-Ⅲ and ClinicalSTS, were selected for analysis to construct five types of medical text classification tasks, and the performance of all models under different structural combinations was compared. Results The accuracy, recall rate and F1 score of the case text structured model proposed in this study were 0.92, 0.90 and 0.91 respectively, all of which were approximately 10% higher than those of the traditional bidirectional encoder model. When dealing with long text scenarios exceeding 1000 words, the model’s efficiency has increased by 12%, demonstrating excellent timeliness and scalability. Conclusion This study verifies the effectiveness of deeply integrating multiple structures in enhancing the structured processing ability of case texts, providing a theoretical basis for intelligent medical text analysis.

Objective To establish an interpretable computer model based on clinical knowledge, compare it with the traditional blackbox model, and further improve the effect of the model in the Mayo endoscopic score for ulcerative colitis(UC). Methods A total of 2251 endoscopic images from the Endoscopy Center of the First Affiliated Hospital of Soochow University were collected as the training set and the internal validation set. The pictures were divided into Group 0, Group 1, Group 2 and Group 3 according to the Mayo endoscopic scoring system to construct the black box model. Meanwhile, all the pictures were marked according to five characteristics: ulcer (present or absent), spontaneous bleeding (present or absent), erythema (absent, visible, obvious), vascular texture (normal, blurred, absent), and mucosal fragility (normal, mild, brittle), and a sub-feature model was established. After fusion, an interpretable model was constructed. In addition, external validation was conducted using endoscopic images from the Endoscopy Center of Changshu Hospital Affiliated to Soochow University. In the external validation set, indicators such as calculation accuracy, matthew correlation coefficient (MCC), and Kapa coefficient were used to compare the performance of the interpretable model with that of the black-box model, and the classification index results of two endoscopists with different seniority were also compared. Finally, the Grad-CAM method was used to highlight the regions of the model reasoning basis. Results The accuracies of the four interpretable models based on MobileNet, ResNet, Xception and EfficientNet in the external validation set were 0.765, 0.800, 0.830 and 0.885 respectively. All were superior to the corresponding traditional black-box models of 0.665, 0.705, 0.775, and 0.815. Among them, the interpretability model based on EfficientNet performed best and was also superior to both junior physicians (0.805) and senior physicians (0.870). Conclusion In the Mayo endoscopic grading diagnosis of ulcerative colitis under endoscopy, the interpretable model performs better than the traditional deep learning black box model. Interpretable models have good application value in the endoscopic diagnosis of UC in the future.

Objective To predict stage Ⅰ-Ⅱ osteonecrosis of the femoral head (ONFH) through radiomics nomograph based on digital radiography (DR) of the hip joint, so as to expand the application scope of conventional DR in the assessment of phase Ⅰ-Ⅱ ONFH. Methods Sixty-one patients with ONFH and 24 healthy volunteers were selected as the research subjects. All patients and healthy volunteers underwent DR and MRI scans of the hip joint. A total of 1409 radiomics features were extracted from the artificially labeled regions of interest in DR images. Feature selection was carried out using the minimum absolute contraction selection operator regression method to construct a multilayer perceptron (MLP) and support vector machine (SVM). The two machine learning classification models were used for ONFH detection. Combining radiomics scores and independent demographic data, radiomics nomoplots were established through logistic regression analysis, and the diagnostic performance of all models was evaluated by indicators such as the receiver operating characteristic curve and its area under the curve (AUC), accuracy, specificity and sensitivity. Results All the research subjects were randomly divided into the training set (n=58) and the validation set (n=27). In the validation set, the AUC of the MLP and SVM radiomics models was 0.980 and 0.954 respectively, and the AUC of the radiomics nomogram was 0.981. Conclusion Machine learning based on the radiomics characteristics of DR is helpful for screening high-risk populations of stage I-II ONFH.

Objective To solve the problem that the fault features of medical imaging equipment are highly concealed, and the single support vector machine (SVM) method is difficult to effectively extract deep-level fault features, resulting in a low Kappa coefficient for fault classification, to propose a fault classification method for CT medical imaging equipment based on particle swarm optimization SVM. Methods Multi-type sensors were used to monitor the running state signals of CT medical imaging equipment in real time. The collected signals were processed through wavelet transform to remove noise and extract effective features, and then the processed signals were input into the deep belief network. By stacking restricted Boltzmann machine layer by layer and going through two stages of unsupervised training and supervised parameter adjustment, the deep characteristics of CT medical imaging equipment faults were captured and learned by deep belief network accurately. The extracted fault features were input into the multi-classifier based on particle swarm optimization SVM, and the fault classification of CT medical imaging equipment was achieved through the trained model. Results The experimental results showed that the F1 score was 0.925, the Kappa coefficient was 0.895, and the Hamming distance was lower than 0.053 on the G2 dataset when the number of deep confidence network layers was 4 and the number of neurons in input, hidden and output layers was 80, 150 and 80 respectively. Conclusion The method proposed in this paper can achieve precise classification of faults in CT medical imaging equipment, providing strong technical support for the fault diagnosis and maintenance of medical imaging equipment.

Objective To evaluate the performance differences between domestic and imported brand ultrasound diagnostic equipment in clinical settings and provide a basis for the clinical selection and use of ultrasound diagnostic equipment, to conduct a comparative analysis of the sensitivity and center frequency of ultrasound probes. Methods Based on the pulse-echo method, through FirstCall 2000 and the self-developed ultrasound probe detection system, a comparative study method was adopted. Fifty-four ultrasound probes in clinical use were randomly selected. Two key indicators, namely sensitivity and center frequency, which have a significant impact on the performance of the probes, were chosen to construct the evaluation criteria, and the detection results of the ultrasound probes were analyzed and evaluated. Results The study found that there was no statistically significant difference in the sensitivity of abdominal probes between domestic and imported brands (P>0.05). When the service life reached 5 years or more, the sensitivity of domestic shallow probes was superior to that of imported brands, and the difference was statistically significant (P<0.05). In addition, there was no statistically significant difference in the center frequency deviation between domestic and imported probes (P>0.05). Conclusion This study provides scientific methods and data support for evaluating the performance of domestic ultrasound probes, offers a research foundation for the consistency evaluation of clinical effectiveness and performance detection of ultrasound diagnostic equipment, and is conducive to establishing a more complete re-evaluation mechanism for in-use ultrasound in clinical practice.

Objective To improve the accuracy of medical equipment condition monitoring and reduce the false alarm rate, to propose a monitoring method for abnormal operating conditions of medical equipment based on multi-source data analysis. Methods The operation data of multi-source medical equipment were collected by sensors, and the soft threshold of operation state was calculated and the fluctuation range was determined. The operation status data of multi-source medical equipment were fused by using the correlation matrix. The time domain features and frequency domain features of the data were extracted based on the data fusion results, and the data state features were mined. By calculating the characteristic entropy value of the running state data and the running state value, the equipment was judged whether it was in an abnormal state. The medical equipment abnormal state ratio was calculated to classify different types of abnormal states. Results The experimental results showed that the average false alarm rate of this method in practical application was 3.25%. Conclusion This method has a high monitoring accuracy and can effectively improve the monitoring accuracy and reduce the false alarm rate.

Objective To conduct continuity detection on three modules in the software using the TQA tool of the helical tomoaccelerator, and to observe and analyze the stability of the dynamic lead door. Methods The data required by the three modules of TQA were collected by using the built-in detector and ionization chamber of Radixact. In the Daily QA module, the stability of the field width (J01 and J07) and the consistency of the dynamic Jaw were observed by using the measured values of the field width constancy (FWC) and the maximum jaw encoder error (MJEE). In the Field Width-dynamic Jaws module, the stability measurement of the field widths of four fields (J42, J20, J14, J07) in symmetrical and asymmetrical conditions was completed by using the Gamma index maximum (GIM) and field width percent difference (FWPD). The time deviation and relative jaw fluence output factor (RJFOF) were calculated in the Jaw Sweep-Dynamic Jaws module to observe the field width stability, dynamic Jaw time accuracy, Jaw dynamic scan stability and dynamic Jaw velocity accuracy. Results In the Daily QA module, the FWC of J01 was 98.88%±0.67%, which was within the normal range of 95% to 105%, and showed a relatively stable state. The FWC of J07 was 99.75%±0.17%, which was within the normal range of 98% to 102%. The fluctuation range of MJEE of the front and rear Jaw over time was -0.3 to 0.2, indicating that the motion error of the front and rear Jaw was very small. According to the changes of 10 states of 4 different Jaw widths in the Field Widths -Dynamic Jaws module over time, it could be known that the GIM of FW was all within the normal tolerance range of 0 to 1, and FWPD was also within the tolerance range of -1 to 1. The fluctuation of Jaw Width over time was relatively small. The response rate of the Jaw in the Jaw Swept Dynamic Jaws module remained stable over time, which was (-0.006±0.003) s, and that of RJFOF J20 was 0.999757±0.000557. The RJFOF J14 was 0.999844±0.000662, and the RJFOF J07 was 0.998641±0.001008, indicating that the output factor value of the injection quantity hardly changed. The corresponding field widths of the three modules were all within the tolerance range, the positioning accuracy error was at the micrometer level, the Jaw response time was extremely short, and the RJFOF value was close to the ideal value of 1. Conclusion The dynamic Jaw changes relatively stably over time, which can provide technical support for giving full play to its advantages in clinical practice.

Objective To construct a cloud pathology service platform to optimize patient pathology services, enhance service efficiency and convenience, and reduce the time and economic costs for patients. Methods A B/S software architecture system was employed, with the front-end developed using the VUE framework and the back-end using the Spring Boot+Spring+MyBatis micro-services framework in this platform. The platform’s functions included a cloud pathology mini-program, cloud pathology service management, pathology data management system, pathology data governance system and pathology data security management system. Data from the three months prior to the system’s launch (May to July 2024) were used as the control group, and data from the three months after the system’s launch (August to October 2024) were used as the experimental groups, and compared the level of relevant work efficiency indicators before and after the system applied. Results Compared with the control group, the experimental group experienced an average reduction of 1.60 d in the time to obtain slides, elimination of slide return and on-site processing, an increase in timeliness satisfaction from 70.59% to 92.52%, an improvement in service quality satisfaction from 70.30% to 93.24%, and an enhancement in satisfaction with the medical process from 72.19% to 96.72%. Conclusion The construction of the cloud pathology service platform has increased the convenience and efficiency of patient borrowing of pathology slides, reduced the risk of damage and loss of pathology slides, and improved patient satisfaction.

Objective To establish a management model for volume-based procurement of medical consumables and develop a monitoring and analysis system, so as to further enhance the efficiency and regulatory effectiveness of volume-based procurement management of medical consumables in medical institutions. Methods The waterfall development model and Spring Boot as the main framework were adopted, combined with open-source technologies. DataX was used for data integration, DataEase for data presentation, while MySQL and Doris were employed for storing metadata and analytical data respectively. Based on a service-oriented architecture, a 4-layer system was constructed, and 3 statistical models were designed. Heterogeneous data were collected via DataX, with unified coding implemented and encrypted transmission ensured. After data cleaning, multidimensional presentation and application of volume-based procurement data were achieved. Results The system constructed in this study enabled intuitive display, monitoring analysis, and intelligent evaluation of multi-dimensional data in the management of volume-based procurement of medical consumables. After the application of the system, the average statistical time for each link in forming the completion report of the coronary stent centralized procurement project was significantly reduced; the brand completion rates of the agreed volumes in five centralized procurement projects (coronary stents, vena cava filters, single-use nonabsorbable polymer ligation clips, pressure pumps, and coronary guiding catheters) were significantly higher than those before the system application, with differences being statistically significant (P<0.05). Conclusion The management model for volumebased purchasing of medical consumables established and designed in this study can provide data support and decision-making basis for the management of volume-based procurement of medical consumables, effectively improving the efficiency and quality of such management.

Objective To optimize surgical arrangement through an intelligent surgical scheduling system, thereby improving operating room utilization and patient satisfaction. Methods The system was built on a data middle platform, adopting SQL Server 2016, Visual Studio 2019, and C# to construct a B/S architecture with a front-end and back-end separation based on Vue+.Net Core. An intelligent algorithm including operating room pre-allocation, doctor-operating room mapping, and surgical sequencing and scheduling was designed, and 6 major modules were developed to realize automatic and manual surgical scheduling. A total of 13313 pieces of intelligent scheduling data from April to September 2024 were selected as the observation group, while 12442 pieces of manual scheduling data from the same period in 2023 served as the control group (with similar numbers of nurses and operating rooms). Eight evaluation indicators were compared between the two groups. Results The intelligent surgical scheduling system based on the data middle platform has realized the intelligent management of surgical scheduling and staff scheduling, and has also achieved the functions of intelligent reminders based on scheduling results and intelligent analysis of operating room services. Clinical application showed that compared with the period before the system was applied, the preoperative waiting time was reduced by 16%, nurses’ overtime hours decreased by 16%, surgical scheduling efficiency increased by 62%, the frequency of surgical adjustments decreased by 35%, the incidence of surgical errors and omissions reduced by 60%, the daily average number of surgeries increased by 8.2%, patient satisfaction rose by 1.3%, and the surgical on-time rate improved by 22.5%, all these indicator differences are statistically significant (P<0.05). Conclusion The intelligent surgical scheduling system is an important tool in modern hospital management. It can optimize surgical scheduling, improve operating room utilization, reduce surgical delays, and enhance patient satisfaction through intelligent and automated means.

Objective To compare and analyze the clinical use of drug-coated balloon (DCB) before and after centralized procurement (hereinafter referred to as “centralized procurement”) based on real-world evidence, so as to provide references for hospital centralized procurement and rational use of high-value consumables. Methods A retrospective study method was used to analyze the patient case data within 2 years before and after the implementation of the drug coated balloon centralized procurement policy. The average hospitalization days, the number of drug-coated balloons used, the treatment follow-up, the main diagnosis of discharge, cost indicators, and the coronary stent / DCB consumption ratio before and after the centralized procurement were compared. Results The average hospitalization time after centralized procurement was reduced by 1.04 d compared to before, from (7.47±2.66) d before centralized procurement to (6.43±2.07) d, with a decrease of 13.9% (P<0.001). The centralized procurement policy effectively reduced the economic burden on patients, and all cost indicators showed a significant decrease. Among them, hospitalization expenses decreased by 24997.15 yuan per case, a decrease of 35.7% (P<0.001). The average cost of consumables decreased by 22929.99 yuan, a decrease of 47.3% (P<0.001). The average cost of DCB decreased by 16437.27 yuan, a decrease of 59.5% (P<0.001). Except for DCB, the total cost decreased by 8559.89 yuan, a decrease of 20.2% (P<0.001). Except for DCB, the material costs have decreased by 6492.73 yuan, a decrease of 31.1% (P<0.001). The policy of centralized procurement has affected the priority and clinical use strategies of DCB in different diseases. After centralized procurement, the proportion of DCB used in different diseases in the main diagnosis of discharge has changed compared to before centralized procurement (P<0.001). The consumption ratio of coronary stent/DCB in patients undergoing percutaneous coronary intervention decreased from 30.68 before collection to 1.97. Conclusion The implementation of drug-coated balloon centralized procurement can shorten the average hospitalization days, reduce the expenses of hospitalized patients, change the structure of hospitalization expenses, promote the clinical application of new technologies and new consumables, optimize the allocation of medical resources, and improve the efficiency of medical work.

Objective To conduct multidimensional comprehensive evaluation as well as analysis of strength and weakness, based on the established index system of medical imaging dynamic acquisition techniques, so as to provide a decision-making foundation for selection of dynamic acquisition techniques. Methods Three types of acquisition techniques were arranged in hospital environment, including interconnection based on log analysis, interconnection based on host image recognition and data collection based on manual operation by original equipment manufacturers. Meanwhile, according to the established index and weight of the evaluation system through systematic information retrieval and expert consultation in the early stage, evaluation results of three different technologies were then analyzed using comprehensive scoring method. Results During the same time period, all three technologies completed the acquisition of operating status data of large-scale imaging equipment. The multi-dimensional evaluation (covering 5 first-level indexes, 14 second-level indexes, and 36 third-level indexes) showed that the operation log-based acquisition technology had a relatively high comprehensive score and was relatively dominant in dimensions such as interactivity, security, and traceability; the host image recognition-based technology and the equipment original system-based technology each had their own advantages and disadvantages; in addition, all three technologies had room for improvement at the third-level index level. Conclusion Acquisition technique based on log analysis gains a higher score and advantage over the other two in multiple dimensions. When it comes to evaluation results in terms of tertiary indexes, all of the three techniques have room for improvement and it is suggested to form complementary strength through advantage integration.

Objective To construct a safety risk assessment system for holmium laser equipment, identify the key factors for safety risk control of holmium laser devices, and develop corresponding risk control measures, to provide certain reference research value for the safe application of holmium laser equipment in surgery and standardized analysis for scientific mathematical models about the risk assessment and control of adverse events in medical devices. Methods Based on the theory, regulatory standards, and literature review of holmium laser equipment, safety risk factor indicators of holmium laser equipment were identified through the analysis of adverse event data of holmium laser equipment in Shandong Province from January 2019 to February 2024; Using the Delphi method to conduct three rounds of inquiry among the 22 selected clinical application experts of holmium laser, a holmium laser safety evaluation system was constructed; Based on the analytic hierarchy process-fuzzy comprehensive evaluation (AHP-FCE) model, the weight values of indicators at each level were determined, and the fuzzy comprehensive evaluation of indicators at each level was carried out. Results A safety risk assessment system for holmium laser was established, which includes 5 primary indicators and 31 secondary indicators. According to the constructed AHP-FCE model, based on the principle of maximum membership degree, the evaluation results of the secondary indicator single factor B3 internal optical transmission system, B4 external optical transmission system, and C6 fiber usage frequency were high-risk factors. Conclusion The safety risk assessment system model of holmium laser constructed based on AHP-FCE method in this study is scientifically reliable, and the evaluation results objectively conform to the actual application situation. It can provide certain reference value for the construction and analysis of scientific models for the safe application of holmium laser surgery and the risk assessment and control of adverse events in medical devices.

Objective To analyze the distribution characteristics and development trends of recall events of passive medical devices in China, and provide a scientific basis for quality control of medical device manufacturing/agent enterprises and post-marketing supervision decisions of regulatory authorities. Methods Taking the recall events of passive medical devices released on the official website of the National Medical Products Administration from 2021 to 2024 as the research objects, data were systematically collected by establishing clear inclusion and exclusion criteria, and analyzed from five dimensions: recall level and quantity, risk classification of recalled devices, type of recalled products, cause of recall, and origin of recalled products. Results A total of 490 recall events of passive medical devices were reported in China from 2021 to 2024, with the number decreasing year by year (213 cases in 2021 and 73 cases in 2024), and voluntary recalls were dominant (only 1 mandatory recall). Among recall levels, Crade Ⅲ recalls accounted for the highest proportion (68.57%); among risk classifications, Class Ⅲ devices accounted for the highest proportion (53.06%). For product types, injection, nursing and protective devices were the most recalled (37.35%), and non-compliance with standards was the primary cause of recalls (accounting for approximately one-third). In terms of origin, the proportion of recalled imported products (62.45%) was higher than that of domestic products (37.55%), and only in 2021, the number of recalled domestic protective devices exceeded that of imported ones. Conclusion Passive medical devices still carry certain risks after being registered and marketed, highlighting the need for continuous strengthening of post-market supervision. Manufacturers, agents, and other relevant enterprises must enhance their sense of responsibility.

Objective To explore and summarize the research status, hot spots and trends of SPD management mode in medical consumables, visual analysis tools were used. Methods Using CNKI Core Database as the literature data source and focusing on literature in the field of SPD management model published from 2016 to 2024 as the main analysis object, this study employs CiteSpace 6.3.R1 software to analyze literature publication trends, authors, research institutions, and keywords in this domain, and generates relevant visual mapping. Results The relevant academic achievements were first published in 2016, and the number of papers has been on the rise in recent years. Most of the research institutions are concentrated in the southern region, while the research institutions in the northern region are relatively few. The highest frequency of occurrence is “medical supplies” (89 times), “fine management” (45 times), “medical supplies management” (19 times), and the central value of such keywords is also high. The research on the SPD distribution model for medical consumables in China began in 2016, which is relatively late. From 2016 to 2019 was the initial stage of the SPD distribution model, mainly focusing on the changes in hospital logistics management, and replacing the methods of entry and exit from the warehouse, acceptance, and requisition through the SPD model. In recent years, hospitals have begun to pay attention to the refinement of medical consumables, including automatic reordering, real-time tracking, and rapid response, and gradually extended from management to management plus supervision. For medical institutions with campuses, the SPD model helps to reduce duplicate construction. Conclusion The SPD model has great potential in optimizing medical material management and improving hospital operational efficiency while ensuring data security.

Objective To further standardize the procurement process, ensure procurement quality, and improve hospital management efficiency, this study constructs a quality control and evaluation index system for tender procurement management, aiming to provide scientific basis and practical guidance for the standardized and refined development of hospital tender procurement management. Methods By searching and analyzing relevant policy documents on hospital bidding and procurement management and related literature on procurement management quality control, the preliminary evaluation index system for bidding and procurement management quality control was extracted and summarized. The Delphi method was adopted to consult 16 experts with rich experience in the relevant field. According to the index screening criteria and expert feedback, the final evaluation index was established. At the same time, the analytic hierarchy process was used to construct a hierarchical structure model and calculate the weight of each evaluation index. Results After two rounds of expert consultation, the evaluation system indicators were finally determined, covering 5 primary indicators and 19 secondary indicators. All determined indicator weights have passed consistency tests. Conclusion The evaluation indicator system constructed in this study is scientific and reasonable, aiding hospitals in controlling the quality of tender procurement management, ensuring fairness, justice, and transparency in the procurement process, and thereby enhancing the overall management level of the hospital.

Objective To ensure the safety of hospital fund utilization, clinical diagnosis and treatment, and patient services, establish a risk prevention and control system for the whole process management of procurement internal control in public hospitals, and propose suggestions for risk prevention and control measures, providing practical reference for the field of hospital procurement management. Methods This study formed a preliminary framework through questionnaire surveys and expert group meetings. The Delphi expert consultation method was used to modify and improve the risk framework, and corresponding control measures were developed. Results The effective response rate of the two rounds of expert consultation was 100.00%, with an expert authority coefficient of 0.88. The average coefficient of variation and expert coordination coefficient for two rounds of expert consultation were 0.1723, 0.1449, and 0.311, 0.384 respectively. The risk framework constructed includes 50 items across 3 main procurement stages and 16 key links. Corresponding control measures have been established for 50 risk points. Conclusion The construction of a risk prevention and control system for the whole process management of procurement internal control in public hospitals is complete, scientific, reliable, practical, and feasible, and has good reference value for internal control management in public hospital procurement.

Objective To explore the application value of artificial intelligence compressed sensing (ACS) technology in single hip joint magnetic resonance imaging (MRI) examinations under different coil conditions. Methods Thirty healthy volunteers were prospectively recruited. Multi-sequence scans of the single hip joint were performed using three protocols: a large ultra-soft coil with parallel imaging (PI) technology, a large ultra-soft coil with ACS technology, and an ultra-soft body coil with ACS technology. For the PI group, ACS group, and body coil ACS group, the signal intensity of anatomical structures (including the femoral head and gluteus medius) and background noise were measured, and the signal to noise ratio (SNR) and contrast to noise ratio (CNR) were calculated. Two radiologists conducted subjective scoring of the images in terms of overall image quality, tissue structure visualization, fat suppression effect, and image artifacts. The Friedman rank-sum test was used for statistical analysis of the subjective and objective evaluation results of the three groups. Results There was no statistically significant difference in the subjective image quality scores between the ACS group and the PI group (P>0.05). In the body coil ACS group, the overall image scores of the sagittal PDWI sequence and coronal PDWI sequence showed statistically significant differences compared with those of the PI group and ACS group (P<0.05). In terms of artifact scores, the body coil ACS group scored lower than the ACS group in the axial, sagittal, and coronal PDWI sequences, with statistically significant differences (P<0.05). In the objective data, except for the SNR of muscle in the axial PDWI sequence, the other SNR and CNR values of the ACS group were higher than those of the PI group and body coil ACS group. For the ACS group, there was no statistically significant difference in the muscle SNR and CNR of the coronal PDWI and coronal T1 WI sequences compared with the PI group (P>0.05), while statistically significant differences were observed in other sequences (P<0.05). Additionally, there was no statistically significant difference between the ACS group and the body coil ACS group in the femoral head SNR, muscle SNR, and CNR of the axial PDWI sequence, as well as the femoral head SNR of the coronal PDWI sequence (P>0.05), but statistically significant differences were found in other sequences (P<0.05). The overall scanning time of the ACS group was 45.3% shorter than that of the PI group. Conclusion ACS technology offers good image quality and significantly shortened scanning time in single hip joint MRI. In some sequences, the image quality of ACS technology with an ultra-soft body coil is comparable to that with a conventional coil, so it can be used when the patient’s condition is not suitable for a large ultra-soft coil.

Objective To explore the value of spectral CT’s single-energy imaging, spectral curve, and atomic number in the diagnosis of negative gallbladder stones. Methods Imaging data of 76 patients with suspected negative gallbladder stones were retrospectively collected, and all patients underwent cholecystectomy, with surgical results as the reference standard. Differences in 40 keV singleenergy images, spectral curve slopes, and effective atomic numbers between negative gallbladder stones and bile were compared. The diagnostic efficacy of 40 keV single-energy images, spectral curves, and effective atomic numbers for distinguishing negative gallbladder stones from bile was analyzed using receiver operating characteristic (ROC) curves. Results At 40 keV, the effective atomic number of negative gallbladder stones was 6.12±0.37, while that of bile was 7.45±0.41, with a statistically significant difference (P<0.05). The CT value of negative gallbladder stones was (-40.12±12.67) HU, and that of bile was (5.78±14.89) HU, showing a statistically significant difference (P<0.05). The spectral curve slope of negative gallbladder stones was -1.58±0.39, compared with 0.27±0.12 for bile, with a statistically significant difference (P<0.05). ROC curve analysis showed that the areas under the curve of 40 keV single-energy images, spectral curves, and atomic number maps were 0.940, 0.951, and 0.974, respectively, with sensitivities and specificities of 88.89% and 84.21%, 92.31% and 91.12%, 100% and 96.11%. Conclusion Spectral CT multiparametric imaging is helpful for early detection of gallbladder stones, guides clinical treatment decisions, reduces the risk of misdiagnosis and missed diagnosis, and has a positive impact on patient treatment and prognosis.

Objective To explore the optimal combination of pre- and post-weights for adaptive statistical iterative reconstruction-V (ASIR-V) in cranial computed tomography (CT) examinations. Methods Ninety patients undergoing cranial CT plain scans were divided into groups A, B, and C (30 cases each) using the random number table method. Pre-ASIR-V weights of 20%, 30%, and 40% were preset for groups A, B, and C before scanning, respectively. After scanning, image reconstruction was performed with post-ASIR-V weights of 50%, 60%, 70%, and 80%, yielding subgroups A5-A8, B5-B8, and C5-C8. Radiation dose parameters (DLP, CTDIvol), effective dose (ED), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were recorded. Two radiologists conducted subjective image evaluation using a 5-point scale in a double-blinded manner. Results In objective evaluation, ED decreased linearly with increasing pre-ASIR-V weight (regression equation: y=-0.33x+2.71, r²=0.918, P<0.001). SNR and CNR in all subgroups increased with higher post-ASIR-V weights (P<0.001). Subjective scores showed a trend of first increasing then decreasing; subgroups A6, B7, and C7 had the highest scores at their respective pre-ASIR-V levels, with subgroup B7 scoring the highest overall. Conclusion At a noise index of 3 and tube voltage of 120 kV, using 30% pre-ASIR-V and 70% post-ASIR-V weights in cranial CT reduces noise, improves image quality, and significantly lowers patient radiation dose.

Blood gas analysis is widely applied in medicine, with a development history of over 200 years. Currently, the commonly used clinical method for blood gas analysis is invasive blood gas detection technology. Although this technology has been well-developed, it still presents numerous issues in clinical practice, such as infection, bleeding, and discontinuous monitoring caused by invasiveness. To address the limitations of invasive techniques, non-invasive blood gas monitoring technology has emerged and continued to evolve. Traditional non-invasive technologies, such as pulse oximeters and capnogram, have limitations in accuracy. Among new technologies, gas chromatography-mass spectrometry, tunable diode laser absorption spectroscopy, and photoacoustic spectroscopy have been gradually applied. This paper elaborated on the development history and detection technologies of blood gas analysis, explored the development of non-invasive blood gas analysis technology, with a particular focus on the application of cavity ring-down spectroscopy based on optics in non-invasive blood gas analysis monitoring technology, and prospected the future development direction of non-invasive blood gas analysis technology, aiming to provide references for the research and development of related equipment.

As a crucial method for monitoring children’s growth and development and diagnosing endocrine diseases, bone age assessment is mainly performed by analyzing X-ray images of the hand and wrist. However, the application of traditional X-ray imaging technology is often affected by background interference, which reduces the accuracy of assessment results. In recent years, deep learning technology has been widely applied in the field of bone age image processing, demonstrating significant advantages due to its ability to automatically identify and extract complex features. This paper reviewed the research progress of deep learning in addressing background redundancy in bone age images, focusing on methods such as region-of-interest extraction, background segmentation technology, and attention mechanisms. These methods can effectively eliminate redundant background information and improve the accuracy and efficiency of bone age assessment. Furthermore, this paper discussed the limitations of existing technologies and future development directions, aiming to provide new research ideas and practical guidance for the field of bone age assessment.

Total knee arthoplasty (TKA) is an effective method to treat severe knee lesions, but postoperative rehabilitation treatment is very important. In recent years, the postoperative rehabilitation treatment of TKA has achieved remarkable results. This paper comprehensively expounded the technical methods, including the innovation and optimization of physical therapy, such as early rehabilitation training, muscle strength training, joint range of motion training, etc., and emphasized the important role of rehabilitation AIDS in patients’ self-care and rehabilitation effect. The research progress of rehabilitation treatment after TKA was reviewed to provide reference for clinical practice and improve the quality of rehabilitation and life of patients.

As a key medical device that provides oxygen-enriched or pure oxygen in a hyperbaric environment, large-scale medical oxygen chambers have been increasingly widely used in clinical medicine. They are mainly used for treating hypoxic diseases, promoting wound healing, and alleviating symptoms of various chronic diseases. Their performance and quality are directly related to treatment efficacy and patient safety. This paper reviewed the key performance indicators of large-scale medical oxygen chambers and their influencing factors, systematically analyzed domestic and international methods for evaluating the performance and quality of oxygen chambers, and focused on discussing the research progress and technical specifications in aspects such as chamber structure, sealing performance, oxygen concentration control, environmental stability, and safety testing. Additionally, combined with industry development trends, it analyzed the deficiencies in performance evaluation and prospected for future research directions and technical breakthroughs, including intelligent detection, standardization system construction, and full-life-cycle quality management, aiming to provide references for the research and development, production, and standardization of medical oxygen chambers.

The left atrium not only regulates left ventricular filling volume but also serves as a key biomarker for cardiovascular diseases. After the occurrence of left ventricular diastolic dysfunction, left atrial function undergoes compensatory changes before alterations in left atrial volume and left ventricular function. Left atrial strain can reflect changes in left atrial function throughout the cardiac cycle. Imaging is the only method for evaluating left atrial strain. Therefore, this article reviewed traditional and novel imaging techniques for assessing left atrial strain, including echocardiography, cardiac magnetic resonance, and cardiac computed tomography. It also introduced the application of radiomics in this field, and analyzed the reproducibility of these imaging techniques as well as the feasibility and limitations of their current clinical applications, aiming to provide appropriate imaging techniques for personalized assessment of left atrial strain in patients, offer reliable diagnostic and therapeutic evidence for clinicians, and facilitate the diagnosis, prognostic evaluation, and formulation of treatment plans for cardiovascular diseases.

The management of medical consumables is a key task in deepening the reform of the medical and health system, and the governance of high-value medical consumables in particular is crucial for standardizing the medical market and safeguarding patients’ rights and interests. Currently, research on the full-life-cycle management of medical consumables has expanded from single-institution logistics management to a multi-dimensional approach, yet significant gaps remain. Specifically, it is difficult to align the intentions of stakeholders, and the interest conflicts among the four parties-government, medical institutions, enterprises, and patients-in areas such as policy implementation, cost control, and quality assurance have not been systematically resolved. This leads to prominent issues including an unclear market operation mechanism and information asymmetry, which hinder the rational allocation of medical resources. Against this backdrop, this paper, from the perspective of stakeholders, identified the four core stakeholder groups, sorted out their research status and interest demands across all stages of the medical consumables’ full life cycle including R&D, production, circulation, usage, and supervision & evaluation, and analyzed the points of interest conflict. Finally, targeted optimization suggestions were proposed, aiming to provide a scientific basis for the formulation of relevant policies, thereby promoting the fair and stable operation of the medical market, reducing interest conflicts, protecting patients’ rights and interests, and advancing the healthy and sustainable development of the medical industry.